Sampling Errors of Climate Monitoring Constellations by Renu

Sampling Errors of Climate Monitoring Constellations by Renu Joseph 1, Daniel B. Kirk−Davidoff 1 and James G. Anderson 2 1 Department of Atmospheric and Oceanic Science and Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 2 Harvard University, Cambridge, MA Standard Deviations of Errors of Single Satellites Goals: Orbits used to sample include: • Set up an observing system that can produce accurate climate statistics of IR brightness temperatures at a wide range of frequencies • Sun-synchronous polar orbits at a range of equator crossing times • Calculate the accuracy that can be achieved in spectrally resolved brightness temperature at a given spatial and temporal resolution • Identify possible empirical relationships to enable prediction of errors on a global scale • 90° inclination “true” polar orbits at various initial longitudes • 60° inclination orbits with more rapid precession For the window channel at the model resolution of 2° x 2. 5° we get Assumptions: • A satellite design capable of making 5 observations per minute, with a circular footprint of about 50 km diameter, with a precision of < 1. 0 K, and an accuracy of < 0. 1 K Can these be predicted? • Use of 1 to a maximum of 4 satellites Relationship of the errors at 909 cm-1 to average time of day, average day of year and average day of half year errors are examined to ensure that the seasonal and diurnal cycles are captured. Methodology and Data: Model derived brightness temperatures are used to calculate the sampling errors. The brightness temperatures are obtained by using MODTRAN on the archived simulations from the GFDL coupled model. Predicted Errors These are then sub-sampled along the paths traversed by the satellite footprint for various potential orbits at different inclinations. Values at each location over the course of the year are grouped together and this establishes the observed brightness temperature. The MODTRAN output for corresponding time period provides the true value. The difference between the observed and true brightness temperatures establishes the accuracy of the retrieval. Examples of different orbits At a higher resolution, the larger number of observations in each grid square allows random weather noise to be overcome. For 15° x 15° grids, errors of the order of 0. 1 K can be obtained for a combination of satellites. Error distributions for different frequencies corresponding to different heights at the 15°x 15° resolution, show that in the lower troposphere, the combination of satellites produce errors of the order of 0. 1 K while in the upper troposphere of 0. 04 K Frequencies chosen to sample a wide range of regions in the atmosphere Error Distribution for Satellite Combinations Conclusions: • It is possible to attain 0. 1 K accuracy in long-term climate averages with a reasonable number of satellites • For a single satellite, the preferred orbit for climate monitoring is a true polar (precessing) orbit, as this substantially reduces errors in mean brightness temperatures, and creates a climate record that is independent of orbital parameters. • A single observatory in a precessing orbit can achieve sampling errors in 15° grid boxes less than 0. 1 K for brightness temperatures in the spectral regions that mostly sample the upper troposphere and lower stratosphere. • A constellation of satellites surely reduces the errors considerably and combinations with precessing polar orbits normally fare better than their sun-synchronous counterparts; For multiple orbiters, precession has large advantages in establishing accurate mean radiances, because a configuration of several sun-synchronous orbiters must sample the diurnal cycle evenly. • It is possible to predict the errors of brightness temperatures at different frequencies if the dominant temporal cycles prevalent in them are known. For instance, in the window channel (909 cm-1) if the diurnal cycle and seasonal cycle are captured, there can be a reasonable expectation of capturing the temperature.